Impact of Shanghai urban land surface forcing on downstream city ...

PUBLICATIONS Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE 10.1002/2014JD022859 Key Points: • Investigate impact of upstream urban land surface on ozone over Kunshan • Urban heat island increases upper air ozone chemistry production • Urban heat island circulation inhibits urban surface ozone advection

Correspondence to: B. Zhu, [email protected]

Citation: Zhu, B., H. Kang, T. Zhu, J. Su, X. Hou, and J. Gao (2015), Impact of Shanghai urban land surface forcing on downstream city ozone chemistry, J. Geophys. Res. Atmos., 120, 4340–4351, doi:10.1002/ 2014JD022859. Received 18 NOV 2014 Accepted 25 MAR 2015 Accepted article online 30 MAR 2015 Published online 5 MAY 2015

Impact of Shanghai urban land surface forcing on downstream city ozone chemistry Bin Zhu1,2, Hanqing Kang1,2, Tong Zhu3,4, Jifeng Su5, Xuewei Hou1,2, and Jinhui Gao1,2 1

Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China, 2Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, China, 3CIRA, Colorado State University, Fort Collins, Colorado, USA, 4NOAA/NESDIS/STAR/JCSDA, College Park, Maryland, USA, 5The 61 Squad of the 94857 Unit of People’s Liberation Army, Wuhu, China

Abstract The urban land surface has a significant impact on local urban heat island effects and air quality. In addition, it influences the atmospheric conditions and air quality in the downwind cities. In this study, the impact of Shanghai urban land surface forcing on weather conditions and air quality over Kunshan was investigated using the Weather Research and Forecasting model coupled with a multilayer urban canopy model and the Community Multiscale Air Quality model. Two simulations were conducted to identify the impact of upstream effects with and without upstream urban land surfaces in control and sensitivity experiments. The results show that the near-surface temperature and boundary layer height over Kunshan increased significantly with the appearance of the upstream urban land surface. Horizontal transport of O3 and its precursors, from Shanghai to Kunshan, are suppressed in the lower boundary layer but are strengthened in the upper boundary layer because of strong urban heat island circulation. As a result, O3 chemical production is decreased in the lower boundary layer of Kunshan but is increased in the upper boundary layer. On average, daytime O3 concentrations over Kunshan are decreased by approximately 2 ppbv in the lower boundary layer but are increased by as much as 40 ppbv in the upper air.

1. Introduction Urbanization processes change the surface energy budget by transforming the natural landscape to artificial constructions. Specifically, energy transfer processes are affected by urban geometry, materials of urban buildings and roads, and anthropogenic activities. Urbanization tends to lower the surface albedo and increases the absorption and the storage of solar radiation and hence, the sensible heat, augment surface friction, and the release of anthropogenic heat, resulting in the urban heat island (UHI) effect [Oke, 1982; Rotach et al., 2005; Allwine et al., 2002]. The UHI effects lead to heat stress in the summer and hence increase the concentrations of air pollutants emitted by extra energy consumption [Akbari, 2005; Banta et al., 1998; Cheng and Byun, 2008]. The urban-induced circulation changes the spatial and temporal distributions of air pollutants in the urban areas. Sarrat et al. [2006] indicated that the enhanced turbulence due to the UHI effect in Paris diluted pollutants more inside the deeper boundary layer (BL). The reduced NOx concentration by enhanced turbulence in the urban BL contributes to the elevated O3 levels through the reduced O3 destruction by NO in the NOx-rich environment [Ryu et al., 2013a]. In addition, the advection process changed by the UHI effects has a high impact on local air pollutants. The land-sea breeze plays an important role in the recirculation/accumulation of O3 concentrations over a coastal city [Levy et al., 2008; Martins et al., 2012]. When O3 precursors emitted from a coastal city are advected to the ocean by land breeze and produce O3 over the ocean, the O3-rich air mass can be advected back to the city by sea breeze. Several studies have found that ozone tends to be continuously produced in the downwind regions of major cities [Kleinman et al., 2003; Tie et al., 2009, 2013]. In such cities, O3 formation is usually under strong volatile organic carbon (VOC)-limited (or NOx-saturated) conditions, which inhibits O3 chemical production. In the downwind region, however, O3 formation gradually shifts to the NOx-limited (or VOC-saturated) condition, which results in pronounced O3 production [Kley, 1997]. ©2015. American Geophysical Union. All Rights Reserved.

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Although the impacts of urban-induced circulation on O3 concentrations for isolated cities were investigated in previous studies [Ryu et al., 2013a; Wang et al., 2007], few have examined the urban influence on

URBAN LAND-SURFACE FORCING ON OZONE

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Figure 1. Weather Research and Forecasting (WRF) modeling domain and location of observation sites: (a) model nested meshes with the horizontal spacing of 13.5, 4.5, and 1.5 km for domain d01, d02, and d03, respectively and (b) land use categories over the innermost domain. The line AB in Figure 1b denotes the location of the vertical cross section shown in Figure 8. The black dots and corresponding names represent locations of meteorological and air-pollutant monitoring sites: Kunshan, KS; Jiading, JD; Hongkou HK; Jingan, JA; Xujiahui, XH; Minhang, MH; and Pudong, PD.

downstream O3 air quality. D. L. Zhang et al. [2009] and Zhang et al. [2011] demonstrated that without the upstream city, the UHI effects over Baltimore would be 1.25°C weaker and the BL would be 200 m shallower, which may change the distribution of air pollutants over Baltimore. Being the largest city and economic center of China, Shanghai has significant impacts on the surrounding meteorological and air quality conditions [Tie et al., 2013; Kang et al., 2014]. However, the contributions of urban land surface and emission on air quality are not clear. Urban areas affect local and downstream air quality mainly through two different ways. First, the meteorological fields and surface properties changed by urban land surfaces change the spatial distribution, chemical reaction, and dry/wet deposition of primary and secondary air pollutants. Second, urbanization processes increase local human activities and hence increase anthropogenic emissions of air pollutants. Both types of effects have crucial and complex impacts on air qualities in local and surrounding areas. In this study, we focus on the first type of effect, which helps us to understand the properties of air pollutant transport, chemistry, and deposition over the surrounding areas influenced by urban surfaces. Kang et al. [2014] investigated the upstream effect of Shanghai on UHI intensity and circulation over Kunshan by using a coupled Weather Research and Forecasting (WRF)-Noah one-layer urban canopy model (UCM). In this study, the WRF model coupled with a multilayer UCM and the Community Multiscale Air Quality (CMAQ) model is used to examine the impacts of the Shanghai urban land surface on O3 concentrations over Kunshan, the downstream city. The objectives are to investigate (1) the impact of upstream urban land surface on the UHI intensity over Kunshan, (2) the changes in horizontal and vertical O3 distributions induced by upstream effects, and (3) the impact of upstream effects on the physical and chemical contributions to O3 concentrations over Kunshan.

2. Model Description and Verification 2.1. Weather Prediction Modeling System The numerical model used for this study is a nonhydrostatic, compressible, two-way interactive Advanced Research WRF [Skamarock et al., 2008] (version 3.3.1) model, coupled with a multilayer UCM building energy parameterization (BEP) [Martilli et al., 2002]. The model is set up with three nested domains (Figure 1a) with horizontal grid spacing (grid numbers) of 13.5 km (181 × 151), 4.5 km (181 × 151), and 1.5 km (100 × 95). The vertical grid contains 30 full sigma levels from the surface to 50 hPa, the lowest 22 levels of which are below 2 km to better resolve the processes within the BL. A 48 h simulation (from 00:00 UTC 11 August to 00:00 UTC 13 August 2013) was conducted with the initial and the outermost boundary conditions from the National Center for Environmental Prediction (NCEP) 1° grid spacing operational Global Forecast System Final Analyses (GFS-FNL). To represent a more realistic urban land type in the

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study area, the fine resolution (30 s) Moderate Resolution Imaging Spectroradiometer (MODIS) 20 category land use data were used. The land use types of the innermost domain are shown in Figure 1b. Two experiments were designed to examine the impacts of upstream urban land surface on the downstream city. The first, known as URB simulation, used MODIS land use as the default for the baseline simulation; the second, NO_SH simulation, was a sensitivity simulation, in which the urban land surface of Shanghai was replaced by cropland. By comparing the two simulations, we can identify the manner in which the Shanghai urban land surface affects local and downstream meteorology. The six-class Purdue Lin scheme [Chen and Sun, 2002] is used for microphysics. The rapid radiative transfer model is used for longwave radiation with six molecular species [Mlawer et al., 1997]. The Goddard scheme was used for shortwave radiation [Chou and Suarez, 1994]. The Mellor-Yamada-Janjić (MYJ) planetary BL scheme [Janjić, 1990, 1994] was used to predict turbulent kinetic energy and to allow vertical mixing between individual layers within the planetary BL. The Eta (similarity theory) surface layer scheme [Janjić, 1996, 2002] in conjunction with the MYJ planetary BL scheme was also used. The four-layer “Noah” land surface scheme [Chen and Dudhia, 2001] provided lower boundary conditions to drive the atmospheric boundary layer in the WRF. A multilayer BEP [Martilli et al., 2002] was coupled to the Noah land surface model to predict the thermal and dynamic urban effects. The multilayer BEP was better able represent the three-dimensional nature of the urban surface than the one-layer UCM. The urban land surface is characterized by building width, canyon width, and building density as a function of height in the Noah-BEP model. The model computes the impact of the horizontal and vertical distributions of buildings on the temperature, wind, and turbulent kinetic energy. The computation of the urban surface temperature considers the shadowing, reflecting, and trapping effects of shortwave and longwave radiations under the urban canyons [Martilli et al., 2002]. 2.2. Air Quality Modeling System In this study, the CMAQ modeling system [Byun and Schere, 2006] version 5.0.1 was used to simulate O3 and its precursors. The output of the WRF-Noah-BEP simulation was provided as the meteorological input for the air quality model. The air quality simulation had the same grid spacing and vertical levels as that in the meteorological simulation for each of the three domains. A 72 h CMAQ simulation (from 00:00 UTC 10 August to 00:00 UTC 13 August 2013) was conducted with the first 40 h used for spin-up for short lifetime chemical species (because local time is 8 h earlier than UTC). It should be noted that the meteorological inputs for the 3 days were derived separately through the method described in section 2.1, in which three 48 h simulations were conducted with the first 24 h used as spin-up time for each simulation. The initial and outmost boundary conditions for CMAQ simulation were obtained from the Model for Ozone and Related Chemical Tracers version 4 (MOZART-4), an off-line global chemical transport model for the troposphere [Emmons et al., 2010]. The boundary conditions for the CMAQ nested domains were extracted from the immediate concentration files of their parent domains. The anthropogenic emissions used in this study were provided by Intercontinental Chemical Transport Experiment–Phase B (INTEX-B) [Q. Zhang et al., 2009] with a horizontal resolution of 0.5° × 0.5° interpolated to 0.1° × 0.1° based on the Transport and Chemical Evolution over the Pacific (TRACE-P) 0.1° × 0.1° emission inventory [Streets et al., 2003]. Even this 0.1° resolution emission inventory is significantly coarser than the innermost grid spacing (1.5 km) and may cause some uncertainties in the simulation. However, the purpose of this study is to investigate the impact of the UHI effects on O3 chemistry and transport. Although the resolution of emission can influence the modeling results to a certain extent, such effects are not crucial to the present study. The natural VOC emission inventory of the Global Emission Inventory Activity 1990 is used for biogenic VOC emissions. We used the Carbon Bond 05 [Whitten et al., 2010] chemical mechanism for gas phase chemistry and the CMAQ six-generation aerosol module [Appel et al., 2013] for aerosol simulation. The process analysis techniques were implemented in the CMAQ modeling system to obtain information that provides the contributions of both physical and chemical processes to simulated species. The details of such process analysis techniques were introduced by Gipson [1999]. The physical and chemical processes discussed in this study include chemistry (CHEM), total advection (TADV), vertical diffusion (VDIF), and dry deposition processes, all of which have important contributions to O3 concentration. ZHU ET AL.


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Figure 2. (a) Observed and simulated diurnal variations of near-surface O3 concentrations on 12 August 2013 at Hongkou (HK), Jingan (JA), Kunshan (KS), Xujiahui (XH), and Pudong (PD) stations marked in Figure 1b. The shaded area indicates the range of simulated O3 concentration at the corresponding locations. The solid and dashed lines represent average observed and simulated O3 concentrations, respectively. (b) Scatterplot of observed and simulated O3 concentrations on 12 August 2013 at the five stations.

2.3. Episode Description The episode we investigated in this study was from 00:00 local time (LT) 12 August to 00:00 LT 13 August 2013. The background meteorological conditions during this episode were analyzed by using weather chart information from Meteorological Information Comprehensive Analysis and Process System (not shown). A high-pressure system prevailed over the East China Sea on 12 August 2013, and Shanghai was located to the west of the high pressure. Under the influence of the high-pressure system, the nearsurface southeasterly breeze in Shanghai remained weak. Therefore, the weather conditions on 12 August 2013 provided favorable conditions for the development of a UHI. Although the prevailing near-surface southeasterly breeze can bring clean air from the ocean to inland, it is also favorable for the advection of air pollutants from Shanghai to its downstream area. On 12 August 2013, the maximum hourly O3 concentration recorded in Shanghai exceeded China air quality standard [Chinese Ministry of Environmental Protection, 2012] Grade II of ~80 ppbv (Figure 2). In Kunshan, the downstream city, near-surface O3 concentrations were higher than that in Shanghai, and the maximum hourly concentration exceeded China air quality standard Grade III at ~100 ppbv. 2.4. Simulation Evaluation The model-simulated surface meteorological variables, O3 and NOx concentrations, were compared with observations obtained from stations in Kunshan and Shanghai. Figure 3 compares the diurnal cycles of surface temperature, wind speed, and wind direction between the simulations and observations recorded by stations Kunshan (KS), Jiading (JD) in Shanghai’s west suburbs, and Minhang (MH) in the center of Shanghai (Figure 1b) during the period of 00:00 LT 12 August to 00:00 LT 13 August 2013. The simulation by the coupled WRF-Noah-BEP model appeared to effectively reproduce the diurnal variation of surface air temperature at KS, JD, and MH. However, the nighttime surface air temperature was underestimated by 2–4°C, likely due to the lack of consideration of anthropogenic heating in the Noah-BEP module; it has been reported that the release of anthropogenic heat can increase the near-surface temperature by approximately 1–3°C [Ichinose et al., 1999; Ohashi et al., 2007; Ryu et al., 2013b]. In addition, the effects of anthropogenic heat have been shown to be more significant in the nighttime than that in the daytime even though anthropogenic heat intensity is generally stronger in the daytime [Fan and Sailor, 2005; Chen et al., 2009]. It should be noted that the peak surface air temperature at KS was approximately 1.4°C and 0.4°C higher than that at MH and JD, respectively. This result is likely due to the strong horizontal advection of warm air from Shanghai to Kunshan.

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Figure 3. Comparison of observed and simulated (a) 2 m air temperature, (b) 10 m wind speed, and (c) wind direction from 00:00 LT 12 August to 00:00 LT 13 August 2013 at Minghang (MH), Jiading (JD), and Kunshan (KS) stations.

The root-mean-square error (RMSE), normalized mean bias (NMB), and normalized mean error (NME) were computed for comparison of the simulated results with the observations. The RMSE, NMB, and NME are calculated, respectively, by equations (1), (2), and (3): " #12 N 1X 2 RMSE ¼ ðMi Oi Þ (1) N i¼1 N X ðMi Oi Þ

NMB ¼

i¼1

N X

100%

(2)

100%

(3)

Oi

i¼1 N X jMi Oi j

NME ¼

i¼1

N X i¼1

Oi i

where Mi represents the simulated value, Oi represents the observational data, and N denotes the number of data pairs. The RMSE of surface air temperature, wind speed, and wind direction were 2.2°C, 0.9 m s1, and 29°, respectively. The NMB and NME for temperature, wind speed, and wind direction were 5% and 6%, 3% and 27%, and 4% and 14%, respectively. Kang et al. [2014] used a coupled WRF-Noah one-layer UCM model to determine that 10 m wind speed is significantly overestimated in the center of Shanghai megacity. The coupled WRF-Noah-BEP model can improve near-surface wind simulation in the urban

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Figure 4. Measured and simulated diurnal variations of (a) NO and (b) NO2 concentrations at Kunshan (KS) station.

area by incorporating a more realistic multilayer UCM. It should be noted that even the multilayer UCM cannot reproduce the wind fields precisely in a sophisticated urban area. Overall, the WRF-simulated surface air temperature, 10 m wind speed, and wind direction agreed reasonably well with the observations in this case. Simulated O3 and NOx concentrations were validated against observations as well (Figures 2 and 4). Figure 2a shows the diurnal cycle of observed surface O3 and the range of simulated results at Jingan (JA), Hongkou (HK), Xujiahui (XH), Pudong (PD), and KS monitoring stations (Figure 1b) during the period from 00:00 LT 12 August to 00:00 LT 13 August 2013. The CMAQ simulations reproduced the diurnal variation trends of O3, with a correlation coefficient of 0.92, passing the 99% significant test. The O3 concentration reached its minimum before sunrise and gradually increased to maximum at noon. The RMSE, NMB, and NME for O3 were 14 ppbv, 19%, and 36%, respectively. Figure 4 gives the comparison of NO and NO2 between the simulation and observation results at KS. The simulation effectively captured the observed diurnal cycles of NO and NO2, with correlation coefficients of 0.87 and 0.57, respectively. The NMB and NME were 13% and 33% for NO and 5% and 27% for NO2, respectively. It should be noted that we interpolated 0.1° × 0.1° emission inventories to 1.5 × 1.5 km resolution to decrease the precision of the modeling results. Simulations may be improved with higher-resolution emission inventories. In general, the CMAQ model performed well in the simulation of O3 and NOx concentrations.

3. Results and Discussion 3.1. Impacts of Upstream Urban Land Surface Forcing on Atmospheric Condition

Figure 5. Daily averaged surface air temperature (°C) and 10 m wind field differences between URB and NO_SH simulations.

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To investigate the impacts of upstream urban land surface forcing on Kunshan’s atmospheric conditions, the results of the URB experiment in this case were compared with those of the NO_SH experiment. Figure 5 shows the differences (URB NO_SH) of daily averaged surface air temperature and wind fields between URB and NO_SH simulations. The temperature difference over Shanghai can be used to characterize the UHI intensity of Shanghai; over Kunshan, it reflects the impact of upstream urban land surface on Kunshan’s temperature. The daily mean UHI intensity over Shanghai was approximately 1–3°C, increasing from southeast to northwest, as a result of the southeasterly breeze. The southeasterly breeze allows warm air to be

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transferred from Shanghai to Kunshan and increases Kunshan’s surface air temperature by 1°C on average. The urban land surface of Shanghai affects the air temperature and the wind field within the BL. In both URB and NO_SH simulations, the southeasterly breeze prevailed on the episode day (Figure 3). Wind field differences between the two simulations showed a convergence trend around the city, which is consistent with the UHI characteristic. It is apparent that the wind speed decreased significantly (3–4 m s1) over Shanghai in the URB simulation due to the sophisticated urban land surface and strong UHI circulation. To better quantify the impacts of Shanghai’s UHI on Kunshan, Figure 6 gives the time series of area-averaged BL height and the temperature profile differences between the URB and NO_SH Figure 6. Time series of the area-averaged air temperature simulations over Kunshan from 00:00 LT 12 August to (°C) difference profiles (color) between URB and NO_SH 00:00 LT 13 August 2013. The surface air temperatures simulations and boundary layer (BL) height (solid and of the URB simulation over Kunshan were 0.5–3°C dotted lines, respectively) over Kunshan for the period of higher than those in the NO_SH simulation, with 00:00 LT 12 August to 00:00 LT 13 August 2013. the maximum difference occurring at approximately 18:00 LT. Warm advection induced by the upstream city had a significant impact on Kunshan’s surface air temperature and influenced the vertical thermal structure, particularly during the daytime. The difference in BL height between the two simulations was very small in the morning and became larger in the afternoon and evening with the maximum difference at approximately 300 m occurring at 17:00 LT. The differences in other O3-product-relevant meteorological parameters such as radiation, clouds, and precipitation over Kunshan between the two simulations were too small for consideration. 3.2. Impact of Upstream Urban Land Surface Forcing on O3 Air Quality The upstream effect influenced local O3 concentration by redistributing O3 through changes in local circulations and by changing O3 chemical process through varied pollutant concentrations and meteorological conditions. In this section, we investigate the impact of modified meteorological conditions on the spatial and temporal distributions of O3 concentrations over Kunshan. During the daytime, Shanghai is under the control of a southeasterly breeze (Figure 3) that brings clean air from the ocean to the city and dilutes O3 concentrations at Shanghai. In addition, Shanghai was found to be in a VOC-limited condition by this and other studies [Tie et al., 2013; Geng et al., 2007], which means that the O3 chemical production processes are inhibited by high NOx concentrations. According to the study by Sillman [1995], the ratio of HCHO/NOy (sum of the total nitrogen species) can be used to identify whether the O3 formation is under NOx-limited or VOC-limited conditions. Their results suggested that when the ratio was larger than 0.28, the O3 formation was under the control of the NOx-limited condition, whereas a ratio smaller than 0.28 indicated O3 formation under the VOC-limited condition. The daytime-averaged (12:00 to 16:00 LT) ratio of HCHO/NOy at the surface of Shanghai was approximately 0.2 in this study. In the farther downwind area of Shanghai, the ratio of HCHO/NOy was approximately 0.8 during the daytime, and the surface O3 concentrations were higher than that in Shanghai (not shown) due to the horizontal advection of O3 from upstream and the pronounced O3 chemical production process in the downstream region [Tie et al., 2013; Li et al., 2012]. Figure 7 shows the differences in averaged surface O3 (color), NOx concentrations (contour line), and wind fields between the URB and NO_SH simulations during the daytime (12:00 to 16:00 LT). The daytimeaveraged surface O3 concentrations over Shanghai increased approximately 10 ppbv with the appearance of the urban landscape. The URB simulation provided a higher BL than that of the NO_SH simulation, which is favorable for diluting primary pollutants such as NOx and hence reducing their near-surface concentrations. In the appearance of the urban surface of Shanghai, chemical processes destructed the

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surface O3 (not shown). As previously mentioned, the Shanghai urban surface is under the control of a VOC-limited condition, and a decrease in NOx concentration will weaken the O3 destruction process. However, in the downwind area of Shanghai, negative differences of O3 concentration between the URB and NO_SH simulations were found in the daytime. To evaluate the effect of Shanghai’s urban land surface on daytime O3 vertical distributions, Figure 8 gives the cross section of O3 and in-plane wind vector differences between the URB and NO_SH experiments along line AB in Figure 1b. The averaged daytime O3 difference shows that O3 concentration increased ~10 ppbv at the surface of Shanghai and decreased ~10 ppbv within the lower BL of Kunshan due to the Figure 7. Difference in averaged surface O3 (color), NOx concentrations (ppbv; contour line), and wind fields urban effect of Shanghai. In the upper BL (>1 km) between URB and NO_SH simulations during the daytime. over both Shanghai and Kunshan, O3 concentrations increased significantly at 20–40 ppbv. The wind field difference between the URB and NO_SH simulation (Figure 8) revealed a strong UHI circulation over the western part of Shanghai in the afternoon. Previous studies also suggested that this urban-induced circulation helps to form an extensive “urban plume” over urban and downstream areas during the daytime [Shou and Zhang, 2010; D. L. Zhang et al., 2009; Zhang et al., 2011]. The prevailing southeasterly breeze was weakened in the lower BL but strengthened in the upper BL as a result of the urban land surface in Shanghai. Therefore, the horizontal transport of the lower boundary layer O3 and its precursors were suppressed by this urban-induced circulation. This also explains why the strongest warm advection from Shanghai to Kunshan occurs in the evening rather than in the afternoon. To evaluate the contributions of the main physical and chemical processes that change the O3 concentration over Kunshan, a process analysis technique was performed. Figure 9 shows the vertical profiles of O3 concentration and its contributions from three main processes (CHEM, TADV, and VDIF) over Kunshan for the period from 12:00 to 16:00 LT. Similar to that in Figure 8, the area-averaged O3 concentrations over Kunshan were decreased by approximately 2 ppbv in the lower BL but were increased as much as 40 ppbv in the upper BL in the upstream city (Figure 9a). Figure 9b reveals that advection and chemical processes were responsible for the decrease/increase of the lower/upper BL O3 over Kunshan in the URB simulation.

Figure 8. Averaged vertical cross section of the difference in O3 concentration (ppbv) and in-plane vectors, where vertical speed is multiplied by 10, between URB and NO_SH simulations.

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The advection process contributed to the decrease in O3 concentration in both simulations over Kunshan (Figure 9b). In the URB simulation, the negative advection contribution decreased with height in the BL and was close to zero in the upper BL. In the NO_SH simulation, a strong negative advection contribution occurred at an altitude of approximately 1 km. The different contributions of the advection processes between the two simulations are closely related to the urban-modified circulation and the upstream O3 concentrations. The urban land surface of Shanghai can slightly increase local daytime O3 concentration within the lower BL (Figure 8), which may enhance the O3 advection contribution to Kunshan. On the contrary, wind speed over Shanghai was slowed by the coarse urban surface and strong


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Figure 9. Daytime-averaged vertical profiles of (a) O3 concentration and (b) contributions of individual processes to O3 concentration over Kunshan in URB (solid line) and NO_SH (dashed line) simulations.

UHI circulations, which may have led to a decrease in O3 advection contribution to the downstream city. The daytime-averaged boundary layer O3 fluxes from Shanghai to Kunshan in the URB and NO_SH simulations were approximately 66 μg m2 s1 and 86 μg m2 s1, respectively. Therefore, the stronger wind speed in the NO_SH simulation resulted in a stronger advection contribution than the URB simulation in the BL. Although the urbanization process led to a significant increment of air pollutant emission and may have produced strong advection contributions to the surrounding areas, the UHI circulation inhibited the horizontal advection of the urban surface pollutants. The UHI circulation, in which the winds converged toward the city center in the lower BL, led to a weaker southeasterly in the northwest part of Shanghai and its downstream city Kunshan under the southeasterly prevailing condition. In the upper BL (800–1800 m), the O3 advection contribution in the URB simulation was higher than that in NO_SH simulation. The URB simulation provided a higher O3 concentration and stronger southeasterly breeze in the upstream of Kunshan (Figure 8), which led to a stronger advection contribution. The averaged upper level O3 fluxes from Shanghai to Kunshan in the URB and NO_SH simulations were 27 μg m2 s1 and 14 μg m2 s1, respectively. The contribution of the chemical process to O3 concentration was negatives at the urban surface in both simulations due to the fast titration effect of high NO emissions. The chemical process contribution increased quickly with height until reaching the maximum of approximately 10–15 ppbv h1. Compared with that in the NO_SH simulation, the chemical process in the URB simulation provided a smaller contribution to O3 concentration in the lower BL. As previously mentioned, the upstream urban effects inhibited the horizontal advection of O3 and its precursors from Shanghai to Kunshan in the lower BL. The NOx concentrations in the URB simulation were lower in the lower BL (800 m) than that in the NO_SH simulation over Kunshan (Figure 10). The URB simulation provided a higher NOx concentration and stronger southeasterly breeze in the upper BL of Shanghai; therefore, the horizontal advection contribution of NOx from Shanghai to Kunshan was increased at this altitude. Moreover, in the upper BL of Kunshan, O3 formation was under the control of the NOx-limited condition (Figure 10). Therefore, the increased NOx concentration in the upper BL of Kunshan in URB simulation resulted in an increment of O3 photochemical production.

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In both simulations, the daytime-averaged vertical diffusion processes contributed to the increase in O3 concentration in the near-surface layer, and the contributions decreased significantly with height in the BL. High O3 concentration occurred in the upper BL, diffusing downward, and hence increasing the near-surface O3. The difference in O3 vertical diffusion contribution between the URB and NO_SH simulations indicates that the contribution increased in the lower BL and decreased in the upper BL by the upstream urbanization effect. Higher O3 concentration in the upper BL in the URB simulation (Figure 8) resulted in a stronger vertical diffusion loss in the upper level and therefore a stronger vertical diffusion compensation to the lower BL.

Figure 10. Daytime-averaged vertical profiles of NOx concentration and the ratio of HCHO/NOy over Kunshan in URB (solid line) and NO_SH (dashed line) simulations.

The dry deposition process is a very important sink of surface O3. The daytime-averaged contributions of dry deposition in URB and NO_SH experiments over Kunshan were 65 and 74 ppbv h1, respectively. This result is attributed to the effects of the upstream city, which decreased the near-surface O3 concentration over Kunshan but also reduced the dry deposition velocity over this region by weakening the turbulent intensity. Because the prevailed southeasterly breeze over Kunshan was weakened by strong upstream UHI circulation, lower wind speed over Kunshan resulted in a weaker turbulent intensity.

4. Conclusions In this study, the impacts of upstream urban land surface forcing on the UHI and O3 air quality over Kunshan were examined by comparing two numerical experiments with and without upstream urban land surface, i.e., the URB and NO_SH simulations. It was determined that the upstream urban surface has a significant impact on the boundary layer structures and circulations over Kunshan and further affects Kunshan’s O3 air quality by redistributing O3 and its precursors. The daily averaged near-surface temperature over Kunshan was approximately 1°C higher with the appearance of Shanghai, the upstream city. The BL height at Kunshan was increased due to the upstream warm advection effect; hence, pollutants were diluted more in the deep urban BL. Acknowledgments This work was supported by grants from the National Natural Science Foundation of China (grant 41275143), the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement 606719 (PANDA project), and the project of the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province, China (12KJA170003). The NCEP GFS-FNL data were obtained from http://rda.ucar.edu/datasets/ds083.2/. The INTEX-B emission inventory data are available at http://cgrer.uiowa.edu/ projects/emmison-data. The MOZART-4 global tropospheric composition data are available at http://www.acd.ucar.edu/ wrf-chem/mozart.shtml. The TRACE-P emission inventory data are available upon request from the author via [email protected].

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Generally, the Shanghai urban land surface forcing decreased lower BL O3 but increased the upper BL O3 concentration over Kunshan at approximately 800–1800 m in height. The urban surface in Shanghai induced strong UHI circulation, which suppressed the horizontal advection of near-surface O3 and its precursors from Shanghai to Kunshan, its downstream city. As a result, O3 chemical production was decreased in the lower BL of Kunshan. However, the UHI circulation promoted horizontal advection of O3 and its precursors from Shanghai to the surrounding areas in the upper BL and consequently increased the upper air O3 photochemical production. Higher O3 concentration in the upper BL, caused by the effects of the upstream city, resulted in a stronger vertical diffusion loss in the upper air and therefore stronger vertical diffusion compensation to the lower BL.

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